Widespread support for a global species list with a formal governance system

Taxonomic data are a scientific common. Unlike nomenclature, which has strong governance institutions, there are currently no generally accepted governance institutions for the compilation of taxonomic data into an accepted global list. This gap results in challenges for conservation, ecological research, policymaking, international trade, and other areas of scientific and societal importance. Consensus on a global list and its management requires effective governance and standards, including agreed mechanisms for choosing among competing taxonomies and partial lists. However, governance frameworks are currently lacking, and a call for governance in 2017 generated critical responses. Any governance system to which compliance is voluntary requires a high level of legitimacy and credibility among those by and for whom it is created. Legitimacy and credibility, in turn, require adequate and credible consultation. Here, we report on the results of a global survey of taxonomists, scientists from other disciplines, and users of taxonomy designed to assess views and test ideas for a new system of taxonomic list governance. We found a surprisingly high degree of agreement on the need for a global list of accepted species and their names, and consistent views on what such a list should provide to users and how it should be governed. The survey suggests that consensus on a mechanism to create, manage, and govern a single widely accepted list of all the world's species is achievable. This finding was unexpected given past controversies about the merits of list governance.

A first checklist of macrofungi for South Africa

Macrofungi are considered as organisms that form large fruiting bodies above or below the ground that are visible without the aid of a microscope. These fungi include most basidiomycetes and a small number of ascomycetes. Macrofungi have different ecological roles and uses, where some are edible, medicinal, poisonous, decomposers, saprotrophs, predators and pathogens, and they are often used for innovative biotechnological, medicinal and ecological applications. However, comprehensive checklists, and compilations on the diversity and distribution of mushrooms are lacking for South Africa, which makes regulation, conservation and inclusion in national biodiversity initiatives difficult. In this review, we compiled a checklist of macrofungi for the first time (excluding lichens). Data were compiled based on available literature in journals, books and fungorium records from the National Collection of Fungi. Even if the list is not complete due to numerous unreported species present in South Africa, it still represents an overview of the current knowledge of the macromycetes of South Africa. The list of names enables the assessment of gaps in collections and knowledge on the fungal biodiversity of South Africa, and downstream applications such as defining residency status of species. It provides a foundation for new names to be added in future towards developing a list that will be as complete as possible, and that can be used by a wide audience including scientists, authorities and the public.

Exploiting opportunistic observations to estimate changes in seasonal site use: An example with wetland birds

Nonsystematically collected, a.k.a. opportunistic, species observations are accumulating at a high rate in biodiversity databases. Occupancy models have arisen as the main tool to reduce effects of limited knowledge about effort in analyses of opportunistic data. These models are generally using long closure periods (e.g., breeding season) for the estimation of probability of detection and occurrence. Here, we use the fact that multiple opportunistic observations in biodiversity databases may be available even within days (e.g., at popular birding localities) to reduce the closure period to 1 day in order to estimate daily occupancies within the breeding season. We use a hierarchical dynamic occupancy model for daily visits to analyze opportunistic observations of 71 species from nine wetlands during 10 years. Our model derives measures of seasonal site use within seasons from estimates of daily occupancy. Comparing results from our "seasonal site use model" to results from a traditional annual occupancy model (using a closure criterion of 2 months or more) showed that our model provides more detailed biologically relevant information. For example, when the aim is to analyze occurrences of breeding species, an annual occupancy model will over-estimate site use of species with temporary occurrences (e.g., migrants passing by, single itinerary prospecting individuals) as even a single observation during the closure period will be viewed as an occupancy. Alternatively, our model produces estimates of the extent to which sites are actually used. Model validation based on simulated data confirmed that our model is robust to changes and variability in sampling effort and species detectability. We conclude that more information can be gained from opportunistic data with multiple replicates (e.g., several reports per day almost every day) by reducing the time window of the closure criterion to acquire estimates of occupancies within seasons.